The preferential elution of ions from melting snowpacks is a complex problem that has been linked to temporary acidification of water bodies. However, the understanding of these processes in snowpacks around the world, including the polar regions that are experiencing unprecedented warming and melting, remains limited despite being instrumental in supporting climate change adaptation.
In this study, data collected from a snowmelt lysimeter and snowpits at meadow and forest-gap sites in a high elevation watershed in Colorado were combined with the PULSE multi-phase snowpack chemistry model to investigate the controls of meltwater chemistry and preferential elution. The snowdepth at the meadow site was 64% of that at the forest-gap site, and the snowmelt rate was greater there (meadow snowpit) due to higher solar irradiance. Cations such as Ca2+ and NH
The Northern High Plains aquifer underlies about 93,000 square miles of Colorado, Kansas, Nebraska, South Dakota, and Wyoming and is the largest subregion of the nationally important High Plains aquifer. Irrigation, primarily using groundwater, has supported agricultural production since before 1940, resulting in nearly $50 billion in sales in 2012. In 2010, the High Plains aquifer had the largest groundwater withdrawals of any major aquifer system in the United States. Nearly one-half of those withdrawals were from the Northern High Plains aquifer, which has little hydrologic interaction with parts of the aquifer farther south. Land-surface elevation ranges from more than 7,400 feet (ft) near the western edge to less than 1,100 ft near the eastern edge. Major stream primarily flow west to east and include the Big Blue River, Elkhorn River, Loup River, Niobrara River, Republican River and Platte River with its two forks—the North Platte River and South Platte River. Population in the Northern High Plain aquifer area is sparse with only 2 cities having a population greater than 30,000.
Droughts across much of the area from 2001 to 2007, combined with recent (2004–18) legislation, have heightened concerns regarding future groundwater availability and highlighted the need for science-based water-resource management. Groundwater models with the capability to provide forecasts of groundwater availability and related stream base flows from the Northern High Plains aquifer were published recently (2016) and were used to analyze groundwater availability. Stream base flows are generally the dominant component of total streamflow in the Northern High Plains aquifer, and total streamflows or shortages thereof define conjunctive management triggers, at least in Nebraska. Groundwater availability was evaluated through comparison of aquifer-scale water budgets compared for periods before and after major groundwater development and across selected future forecasts. Groundwater-level declines and the forecast amount of groundwater in storage in the aquifer also were examined.
Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Effective conservation requires prioritizing areas that are vulnerable to large, irreversible changes. Unfortunately, rigorously documenting these changes with experiments and long-term monitoring is not only costly, but may provide evidence that is too late to facilitate proactive decisions.
We use a simple model to illustrate that commonly available short-term spatial, “snapshot”, data from a given ecosystem along an environmental gradient can be used to identify environmental conditions under which different ecosystem states (e.g. different species compositions) co-occur in space. These environmental conditions are those under which future perturbations have the potential for discontinuous large, sometimes irreversible, effects; and can be mapped in space to predict potential spatial hotspots of ecosystem fragility.
We apply these insights to ecologically important high-elevation subalpine meadows of the Sierra Nevada (California). Our analysis reveals specific areas within meadows that may be more vulnerable than others because their plant communities have the potential to shift to a different state. These shifts can be mechanistically explained by interactions between the vegetation and the local water regimes and/or the upper soil conditions.
Our study provides a simple workflow using commonly available data to help prioritize conservation areas based on their potential sensitivity to upcoming perturbations. Such an approach could be very valuable to make most efficient use of conservation and management resources in the context of ongoing global changes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2019.108388","usgsCitation":"Genin, A., Lee, S.R., Berlow, E.L., Ostoja, S., and Kefi, S., 2020, Mapping hotspots of potential ecosystem fragility using commonly available spatial data: Biological Conservation, v. 241, 108388, 11 p., https://doi.org/10.1016/j.biocon.2019.108388.","productDescription":"108388, 11 p.","ipdsId":"IP-084595","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":457858,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2019.108388","text":"Publisher Index Page"},{"id":385279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sequoia National Park, Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.90527343750001,\n 36.05798104702501\n ],\n [\n -118.3447265625,\n 37.29153547292737\n ],\n [\n -119.36645507812499,\n 38.30718056188316\n ],\n [\n -119.81689453125,\n 38.324420427006544\n ],\n [\n -120.047607421875,\n 37.83148014503288\n ],\n [\n -119.937744140625,\n 37.32648861334206\n ],\n [\n -119.278564453125,\n 36.77409249464195\n ],\n [\n -118.94897460937499,\n 36.20882309283712\n ],\n [\n -118.24584960937499,\n 35.47856499535729\n ],\n [\n -117.87231445312499,\n 35.43381992014202\n ],\n [\n -117.90527343750001,\n 36.05798104702501\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"241","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Genin, Alexandre","contributorId":192956,"corporation":false,"usgs":false,"family":"Genin","given":"Alexandre","email":"","affiliations":[],"preferred":false,"id":814635,"contributorType":{"id":1,"text":"Authors"},"rank":0},{"text":"Lee, Steven R. 0000-0002-4581-3684 srlee@usgs.gov","orcid":"https://orcid.org/0000-0002-4581-3684","contributorId":5630,"corporation":false,"usgs":true,"family":"Lee","given":"Steven","email":"srlee@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":814636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berlow, Eric L.","contributorId":91416,"corporation":false,"usgs":false,"family":"Berlow","given":"Eric","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":814637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ostoja, Steven M.","contributorId":225183,"corporation":false,"usgs":false,"family":"Ostoja","given":"Steven M.","affiliations":[{"id":32922,"text":"USDA California Climate Hub","active":true,"usgs":false}],"preferred":false,"id":814638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kefi, Sonia","contributorId":257566,"corporation":false,"usgs":false,"family":"Kefi","given":"Sonia","affiliations":[{"id":37581,"text":"Université de Montpellier, France","active":true,"usgs":false}],"preferred":false,"id":814639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70205930,"text":"fs20193064 - 2020 - Continuous nitrate monitoring in groundwater and potential contribution to surface-water nitrogen loads in Mason County, Illinois","interactions":[],"lastModifiedDate":"2022-04-19T21:47:50.406624","indexId":"fs20193064","displayToPublicDate":"2020-02-04T09:34:19","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-3064","displayTitle":"Continuous Nitrate Monitoring in Groundwater and Potential Contribution to Surface-Water Nitrogen Loads in Mason County, Illinois","title":"Continuous nitrate monitoring in groundwater and potential contribution to surface-water nitrogen loads in Mason County, Illinois","docAbstract":"Illinois has some of the most productive farmland in the country. The use of fertilizers to improve crop production has increased, which has resulted in an increase in the concentration of nitrogen in many streams and aquifers. The U.S. Geological Survey, in cooperation with the Illinois Environmental Protection Agency, is continuously monitoring (one reading every 15 minutes) the concentration of nitrate plus nitrite, as nitrogen, in a groundwater well and assessing the potential contribution to surface-water nitrogen loads. Continuous monitoring of the nitrate concentration allows for the collection of a larger dataset in comparison to periodic or event-based sampling. This fact sheet describes the data collection methods, describes the overall experimental design, and displays data collected for the study. 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Central Midwest Water Science Center
U.S. Geological Survey
405 N. Goodwin Ave.
Urbana, Illinois 61801
This article assesses the ability of regionally specific, frequency‐dependent crustal attenuation (
Rates of organic carbon (OC) burial in some coastal wetlands appear to be greater in recent years than they were in the past. Possible explanations include ongoing mineralization of older OC or the influence of an unaccounted‐for artefact of the methods used to measure burial rates. Alternatively, the trend may represent real acceleration in OC burial. We quantified OC burial rates of mangrove and coastal freshwater marshes in southwest Florida through a comparison of rates derived from 210Pb, 137Cs, and surface marker horizons (MHs). Age/depth profiles of lignin: OC were used to assess whether down‐core remineralization had depleted the OC pool relative to lignin, and lignin phenols were used to quantify the variability of lignin degradation. Over the past 120 years, OC burial rates at seven sites increased by factors ranging from 1.4 to 6.2. We propose that these increases represent net acceleration. Change in relative sea‐level rise is the most likely large‐scale driver of acceleration, and sediment deposition from large storms can contribute to periodic increases. Mangrove sites had higher OC and lignin burial rates than marsh sites, indicating inherent differences in OC burial factors between the two habitat types. The higher OC burial rates in mangrove soils mean that their encroachment into coastal freshwater marshes has the potential to increase burial rates in those locations even more than might be expected from the acceleration trends. Regionally, these findings suggest that burial represents a substantially growing proportion of the coastal wetland carbon budget.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JG005349","usgsCitation":"Breithaupt, J.L., Smoak, J.M., Bianchi, T.S., Vaughn, D., Sanders, C., Radabaugh, K., Osland, M.J., Feher, L.C., Lynch, J.C., Cahoon, D.R., Anderson, G.H., Whelan, K.R., Rosenheim, B.E., Moyer, R.P., and Chambers, L., 2020, Increasing rates of carbon burial in southwest Florida coastal wetlands: Journal of Geophysical Research: Biogeosciences, v. 125, no. 2, e2019JG005349, 25 p., https://doi.org/10.1029/2019JG005349.","productDescription":"e2019JG005349, 25 p.","ipdsId":"IP-109647","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":457860,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019jg005349","text":"Publisher Index Page"},{"id":437125,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZH3R4G","text":"USGS data 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The integrated biogeochemical model PnET-BGC was applied to 25 forest watersheds that represent a range of acid sensitivity in the Adirondack region of New York, USA to simulate the response of streams to past and future changes in atmospheric S and N deposition, and calculate the target loads of acidity for protecting and restoring stream water quality and ecosystem health. Using measured data, the model was calibrated and applied to simulate soil and stream chemistry at all study sites. Model hindcasts indicate that historically stream water chemistry in the Adirondacks was variable, but inherently sensitive to acid deposition. The median model-simulated acid neutralizing capacity (ANC) of the streams was projected to be 55 μeq L−1 before the advent of anthropogenic acid deposition (~1850), decreasing to minimum values of 10 μeq L−1 around the year 2000. The median simulated ANC increased to 13 μeq L−1 by 2015 in response to decreases in acid deposition that have occurred over recent decades. Model projections suggest that simultaneous decreases in sulfate, nitrate and ammonium deposition are more effective in restoring stream ANC than individual decreases in sulfur or nitrogen deposition. However, the increases in stream ANC per unit equivalent decrease in S deposition is greater compared to decreases in N deposition. Using empirical algorithms, fish community density and biomass are projected to increase under several deposition-control scenarios that coincide with increases in stream ANC. Model projections suggest that even under the most aggressive deposition-reduction scenarios, stream chemistry and fisheries will not fully recover from historical acidification by 2200.
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Extensive meadows of eelgrass (Zostera marina) in southwest Alaska support hundreds of thousands of waterfowl during fall migration and may be susceptible to plant pathogens. We recovered DNA of organisms pathogenic to eelgrass from environmental samples and in the cloacal contents of eight of nine waterfowl species that annually migrate along the Pacific coast of North America and Asia. Coupled with a signal of asymmetrical gene flow of eelgrass running counter to that expected from oceanic and coastal currents between Large Marine Ecosystems, this evidence suggests waterfowl are vectors of eelgrass pathogens.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.6039","usgsCitation":"Menning, D.M., Ward, D.H., Wyllie-Echeverria, S., Sage, K., Gravley, M.C., Gravley, H., and Talbot, S.L., 2020, Are migratory waterfowl vectors of seagrass pathogens?: Ecology and Evolution, v. 10, no. 4, p. 2062-2073, https://doi.org/10.1002/ece3.6039.","productDescription":"12 p.","startPage":"2062","endPage":"2073","ipdsId":"IP-108993","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":457864,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.6039","text":"Publisher Index Page"},{"id":374006,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -166.46484375,\n 53.4357192066942\n ],\n [\n -151.171875,\n 53.4357192066942\n ],\n [\n -151.171875,\n 60.6301017662667\n ],\n [\n -166.46484375,\n 60.6301017662667\n ],\n [\n -166.46484375,\n 53.4357192066942\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Menning, Damian M. 0000-0003-3547-3062 dmenning@usgs.gov","orcid":"https://orcid.org/0000-0003-3547-3062","contributorId":205131,"corporation":false,"usgs":true,"family":"Menning","given":"Damian","email":"dmenning@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":787049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":787050,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wyllie-Echeverria, Sandy","contributorId":224099,"corporation":false,"usgs":false,"family":"Wyllie-Echeverria","given":"Sandy","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":787051,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sage, Kevin 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":139795,"corporation":false,"usgs":true,"family":"Sage","given":"Kevin","email":"ksage@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":787052,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gravley, Megan C. 0000-0002-4947-0236 mgravley@usgs.gov","orcid":"https://orcid.org/0000-0002-4947-0236","contributorId":202812,"corporation":false,"usgs":true,"family":"Gravley","given":"Megan","email":"mgravley@usgs.gov","middleInitial":"C.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":787053,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gravley, Hunter","contributorId":224100,"corporation":false,"usgs":false,"family":"Gravley","given":"Hunter","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":787054,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":787055,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208342,"text":"70208342 - 2020 - Final report to SCEC on the January 8, 2020 SCEC workshop 'Dynamic Rupture TAG Ingredients Workshop – Fault Friction (SCEC Project 19121)'","interactions":[],"lastModifiedDate":"2020-02-05T06:52:10","indexId":"70208342","displayToPublicDate":"2020-02-04T06:51:33","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Final report to SCEC on the January 8, 2020 SCEC workshop 'Dynamic Rupture TAG Ingredients Workshop – Fault Friction (SCEC Project 19121)'","docAbstract":"This workshop was the second of a series of four SCEC5 workshops designed to evaluate the importance of each of the four ingredients required for dynamic earthquake rupture simulations. The four ingredients are: initial stress conditions, fault geometry, rock properties, and fault friction (Figure 1). This workshop included a range of views of how fault friction operates in the Earth, based on information from lab experiments, from field observations, and from dynamic rupture simulations. The participants also learned about two current related SCEC projects: the dynamic rupture code validation project and the surface fault displacement project.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Dynamic rupture TAG ingredients workshop – Fault friction","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Southern California Earthquake Center","usgsCitation":"Harris, R.A., and Barall, M., 2020, Final report to SCEC on the January 8, 2020 SCEC workshop 'Dynamic Rupture TAG Ingredients Workshop – Fault Friction (SCEC Project 19121)', 8 p.","productDescription":"8 p.","ipdsId":"IP-115748","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":372050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372040,"type":{"id":15,"text":"Index Page"},"url":"https://www.scec.org/proposal/report/19121"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Ruth A. 0000-0002-9247-0768 harris@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-0768","contributorId":786,"corporation":false,"usgs":true,"family":"Harris","given":"Ruth","email":"harris@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":781485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barall, Michael 0000-0001-7724-8563","orcid":"https://orcid.org/0000-0001-7724-8563","contributorId":198670,"corporation":false,"usgs":false,"family":"Barall","given":"Michael","affiliations":[],"preferred":false,"id":781486,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70219490,"text":"70219490 - 2020 - Understanding the effect of fire on vegetation composition and gross primary production in a semi-arid shrubland ecosystem using the Ecosystem Demography (EDv2.2) model","interactions":[],"lastModifiedDate":"2021-04-12T11:55:22.924404","indexId":"70219490","displayToPublicDate":"2020-02-04T06:39:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1012,"text":"Biogeosciences Discussions","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the effect of fire on vegetation composition and gross primary production in a semi-arid shrubland ecosystem using the Ecosystem Demography (EDv2.2) model","docAbstract":"Wildfires in sagebrush (Artemisia spp.) dominated semi-arid ecosystems in the western United States have increased dramatically in frequency and severity in the last few decades. Severe wildfires often lead to the loss of native sagebrush communities and change the biogeochemical conditions which make it difficult for sagebrush to regenerate. Invasion of cheat- grass (Bromus tectorum) accentuates the problem by making the ecosystem more susceptible to frequent burns. Managers have implemented several techniques to cope with the cheatgrass-fire cycle, ranging from controlling undesirable fire effects by removing fuel loads either mechanically or via prescribed burns, to seeding the fire-affected areas with shrubs and native perennial forbs. There have been a number of studies at local scales to understand the direct impacts of wildfire on vegetation, however, there is a larger gap in understanding these impacts at broad spatial and temporal scales. This need highlights the importance of dynamic global vegetation models (DGVMs) and remote sensing. In this study, we explored the influence of fir on vegetation composition and gross primary production (GPP) in the sagebrush ecosystem using the Ecosystem Demography (EDv2.2) model, a dynamic global vegetation model. We selected Reynolds Creek Experimental Watershed (RCEW) to run our simulation study, an intensively monitored sagebrush-dominated ecosystem in the northern Great Basin. We ran point-based simulations at four existing flux-tower sites in the study area for a total 150 years after turning on the fire module in the 25th year. Results suggest dominance of shrubs in a non-fire scenario, however under the fire scenario we observed contrasting phases of high and low shrub density and C3 grass growth. Regional model simulations showed a gradual decline in GPP for fire-introduced areas through the initial couple of years instead of killing all the vegetation in the affected area in the first year itself. We also compared the results from EDv2.2 with satellite-derived GPP estimates for the areas in RCEW burned by a wildfire in 2015 (Soda Fire). We observed moderate pixel-level correlations between maps of post-fire recovery EDv2.2 GPP and MODIS derived GPP. This study contributes to understanding the application of ecosystem models to investigate temporal dynamics of vegetation under alternative fire regimes and post-fire ecosystem restoration.","language":"English","publisher":"Copernicus","doi":"10.5194/bg-2019-510","usgsCitation":"Pandit, K., Dashti, H., Hudak, A., Glenn, N.F., Flores, A.N., and Shinneman, D.J., 2020, Understanding the effect of fire on vegetation composition and gross primary production in a semi-arid shrubland ecosystem using the Ecosystem Demography (EDv2.2) model: Biogeosciences Discussions, v. 18, no. 6, p. 2027-2045, https://doi.org/10.5194/bg-2019-510.","productDescription":"19 p.","startPage":"2027","endPage":"2045","ipdsId":"IP-115400","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":457866,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-2019-510","text":"Publisher Index Page"},{"id":384956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.98242187499999,\n 42.13082130188811\n ],\n [\n -114.08203125,\n 42.13082130188811\n ],\n [\n -114.08203125,\n 44.68427737181225\n ],\n [\n -116.98242187499999,\n 44.68427737181225\n ],\n [\n -116.98242187499999,\n 42.13082130188811\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pandit, Karun","contributorId":221464,"corporation":false,"usgs":false,"family":"Pandit","given":"Karun","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":813796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dashti, Hamid","contributorId":257078,"corporation":false,"usgs":false,"family":"Dashti","given":"Hamid","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":813797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hudak, Andrew A.","contributorId":257079,"corporation":false,"usgs":false,"family":"Hudak","given":"Andrew A.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":813798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glenn, Nancy F.","contributorId":195241,"corporation":false,"usgs":false,"family":"Glenn","given":"Nancy","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":813799,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flores, Alejandro N","contributorId":256965,"corporation":false,"usgs":false,"family":"Flores","given":"Alejandro","email":"","middleInitial":"N","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":813800,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":813801,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208657,"text":"70208657 - 2020 - Meteotsunamis triggered by tropical cyclones","interactions":[],"lastModifiedDate":"2020-02-24T19:45:27","indexId":"70208657","displayToPublicDate":"2020-02-03T19:43:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Meteotsunamis triggered by tropical cyclones","docAbstract":"Tropical cyclones are one of the most destructive natural hazards and much of the damage and casualties they cause are flood-related. Accurate characterization and prediction of total water levels during extreme storms is necessary to minimize coastal impacts. While meteotsunamis are known to influence water levels and to produce severe consequences, they have been disregarded during tropical cyclones. This study demonstrates that meteotsunami waves commonly occur during tropical cyclones, and that they can significantly contribute to total water levels. We have discovered that the most extreme meteotsunami events were triggered by inherent features of the structure of tropical cyclones: inner and outer spiral rainbands. While outer distant spiral rainbands produced single-peak meteotsunami waves, inner spiral rainbands triggered longer lasting (~12 hours) wave trains on the front side of the tropical cyclones. We use an idealized coupled ocean-atmosphere-wave numerical model to analyze TC meteotsunami generation and propagation mechanisms.","language":"English","publisher":"Nature","doi":"10.1038/s41467-020-14423-9","usgsCitation":"Olabarrieta, M., Shi, L., Nolan, D., and Warner, J., 2020, Meteotsunamis triggered by tropical cyclones: Nature Communications, v. 11, 678, 14 p., https://doi.org/10.1038/s41467-020-14423-9.","productDescription":"678, 14 p.","ipdsId":"IP-107152","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":457868,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-020-14423-9","text":"Publisher Index Page"},{"id":372595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.822265625,\n 28.613459424004414\n ],\n [\n -96.328125,\n 27.137368359795584\n ],\n [\n -94.5703125,\n 28.459033019728043\n ],\n [\n -91.0546875,\n 28.536274512989916\n ],\n [\n -88.154296875,\n 28.76765910569123\n ],\n [\n -88.154296875,\n 29.6880527498568\n ],\n [\n -86.044921875,\n 29.6880527498568\n ],\n [\n -84.462890625,\n 29.152161283318915\n ],\n [\n -83.75976562499999,\n 27.293689224852407\n ],\n [\n -82.001953125,\n 24.5271348225978\n ],\n [\n -79.716796875,\n 24.766784522874453\n ],\n [\n -80.068359375,\n 28.459033019728043\n ],\n [\n -79.541015625,\n 32.10118973232094\n ],\n [\n -75.234375,\n 35.24561909420681\n ],\n [\n -76.552734375,\n 36.24427318493909\n ],\n [\n -78.134765625,\n 34.66935854524543\n ],\n [\n -80.771484375,\n 32.76880048488168\n ],\n [\n -85.95703125,\n 31.203404950917395\n ],\n [\n -92.548828125,\n 30.90222470517144\n ],\n [\n -97.822265625,\n 28.613459424004414\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":211373,"corporation":false,"usgs":false,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":782920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shi, Luming","contributorId":222697,"corporation":false,"usgs":false,"family":"Shi","given":"Luming","email":"","affiliations":[{"id":40590,"text":"Civil and Coastal Engineering Department, ESSIE, University of Florida Gainesville, FL 32611","active":true,"usgs":false}],"preferred":false,"id":782921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nolan, David","contributorId":222698,"corporation":false,"usgs":false,"family":"Nolan","given":"David","email":"","affiliations":[{"id":40591,"text":"Rosenstiel School of Marine and Atmospheric Science, University of Miami Miami, FL 33149","active":true,"usgs":false}],"preferred":false,"id":782922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":782919,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211679,"text":"70211679 - 2020 - An aeolian grainflow model for Martian Recurring Slope Lineae","interactions":[],"lastModifiedDate":"2020-08-06T23:07:07.093979","indexId":"70211679","displayToPublicDate":"2020-02-03T18:05:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"An aeolian grainflow model for Martian Recurring Slope Lineae","docAbstract":"Recurring Slope Lineae (RSL) on Mars have been enigmatic since their discovery; their behavior resembles a seeping liquid but sources of water remain puzzling. This work demonstrates that the properties of RSL are consistent with observed behaviors of Martian and terrestrial aeolian processes. Specifically, RSL are well-explained as flows of sand that remove a thin coating of dust. Observed RSL properties are supportive of or consistent with this model, which requires no liquid water or other exotic processes, but rather indicates seasonal aeolian behavior. These settings and behaviors resemble features observed by rovers and also explain the occurrence of many slope lineae on Mars that do not meet the strict definition of RSL. This indicates that RSL can be explained simply as aeolian features. Other processes may add complexities just as they could modify the behavior of any sand dune.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2020.113681","usgsCitation":"Dundas, C.M., 2020, An aeolian grainflow model for Martian Recurring Slope Lineae: Icarus, v. 343, 113681, 16 p., https://doi.org/10.1016/j.icarus.2020.113681.","productDescription":"113681, 16 p.","ipdsId":"IP-107848","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":457871,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.icarus.2020.113681","text":"Publisher Index Page"},{"id":377143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"343","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":795041,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70227983,"text":"70227983 - 2020 - Distribution, density, and land cover associations of wintering Golden Eagles in the Southern Great Plains","interactions":[],"lastModifiedDate":"2022-02-03T23:07:32.071966","indexId":"70227983","displayToPublicDate":"2020-02-03T16:49:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Distribution, density, and land cover associations of wintering Golden Eagles in the Southern Great Plains","docAbstract":"In addition to its resident Golden Eagles (Aquila chrysaetos), the Southern Great Plains of North America receives an influx of migrant Golden Eagles each winter. However, little current or quantitative information is available regarding eagle presence or the species' land cover associations across the region. During the winters of 2014/2015 and 2015/2016, we surveyed Golden Eagles along 51 approximately 55-km-long road survey transects within a 136,800-km2 area of the Southern Great Plains of eastern New Mexico and the panhandles of Texas and Oklahoma. Our goal was to estimate the winter density of Golden Eagles in the region and to evaluate their land cover associations. Detections were low, with an estimated regional winter density of 0.31 eagles per 100 km2. We found that Golden Eagles were detected in rangeland cover types in greater proportion, and in agricultural and other land cover types in lesser proportion, to their availability. Our results provide regulatory agencies with data that may facilitate better-informed decision making for eagle conservation in the region.
","language":"English","doi":"10.3398/064.080.0402","usgsCitation":"Mitchell, N., Boal, C.W., and Skipper, B., 2020, Distribution, density, and land cover associations of wintering Golden Eagles in the Southern Great Plains: Western North American Naturalist, v. 80, no. 4, p. 452-461, https://doi.org/10.3398/064.080.0402.","productDescription":"10 p.","startPage":"452","endPage":"461","ipdsId":"IP-099428","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Oklahoma, Texas","otherGeospatial":"Southern Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.05078125,\n 33.578014746143985\n ],\n [\n -97.822265625,\n 33.578014746143985\n ],\n [\n -97.822265625,\n 37.09023980307208\n ],\n [\n -107.05078125,\n 37.09023980307208\n ],\n [\n -107.05078125,\n 33.578014746143985\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mitchell, N.R.","contributorId":274259,"corporation":false,"usgs":false,"family":"Mitchell","given":"N.R.","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":832848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skipper, B.R.","contributorId":270348,"corporation":false,"usgs":false,"family":"Skipper","given":"B.R.","email":"","affiliations":[{"id":56152,"text":"Angelo State University","active":true,"usgs":false}],"preferred":false,"id":832850,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208369,"text":"70208369 - 2020 - Carbon release through abrupt permafrost thaw","interactions":[],"lastModifiedDate":"2020-03-26T12:50:28","indexId":"70208369","displayToPublicDate":"2020-02-03T15:33:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Carbon release through abrupt permafrost thaw","docAbstract":"The permafrost zone is expected to be a substantial carbon source to the atmosphere, yet large-scale models currently only\nsimulate gradual changes in seasonally thawed soil. Abrupt thaw will probably occur in <20% of the permafrost zone but could\naffect half of permafrost carbon through collapsing ground, rapid erosion and landslides. Here, we synthesize the best available\ninformation and develop inventory models to simulate abrupt thaw impacts on permafrost carbon balance. Emissions across\n2.5 million km2 of abrupt thaw could provide a similar climate feedback as gradual thaw emissions from the entire 18 million km2\npermafrost region under the warming projection of Representative Concentration Pathway 8.5. While models forecast that\ngradual thaw may lead to net ecosystem carbon uptake under projections of Representative Concentration Pathway 4.5, abrupt\nthaw emissions are likely to offset this potential carbon sink. Active hillslope erosional features will occupy 3% of abrupt thaw\nterrain by 2300 but emit one-third of abrupt thaw carbon losses. Thaw lakes and wetlands are methane hot spots but their\ncarbon release is partially offset by slowly regrowing vegetation. After considering abrupt thaw stabilization, lake drainage and\nsoil carbon uptake by vegetation regrowth, we conclude that models considering only gradual permafrost thaw are substantially\nunderestimating carbon emissions from thawing permafrost.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41561-019-0526-0","usgsCitation":"Turetsky, M.R., Abbott, B., Jones, M.C., Walter Anthony, K., Olefeldt, D., Schuur, E.A., Grosse, G., Kuhry, P., Hugelius, G., Koven, C., Lawrence, D.M., Gibson, C., Sannel, A.B., and McGuire, A., 2020, Carbon release through abrupt permafrost thaw: Nature Geoscience, v. 13, p. 138-143, https://doi.org/10.1038/s41561-019-0526-0.","productDescription":"6 p.","startPage":"138","endPage":"143","ipdsId":"IP-102621","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":372090,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Turetsky, Merritt R.","contributorId":169398,"corporation":false,"usgs":false,"family":"Turetsky","given":"Merritt","email":"","middleInitial":"R.","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":781621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abbott, Benjamin W.","contributorId":218049,"corporation":false,"usgs":false,"family":"Abbott","given":"Benjamin W.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":781622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Miriam C. 0000-0002-6650-7619 miriamjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":4056,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"miriamjones@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":781620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walter Anthony, Katey","contributorId":192911,"corporation":false,"usgs":false,"family":"Walter Anthony","given":"Katey","affiliations":[],"preferred":false,"id":781623,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olefeldt, David","contributorId":169408,"corporation":false,"usgs":false,"family":"Olefeldt","given":"David","affiliations":[{"id":32365,"text":"Department of Renewable Resources, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":781624,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schuur, Edward A.","contributorId":218050,"corporation":false,"usgs":false,"family":"Schuur","given":"Edward","email":"","middleInitial":"A.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":781625,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grosse, Guido","contributorId":146182,"corporation":false,"usgs":false,"family":"Grosse","given":"Guido","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":781626,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kuhry, Peter","contributorId":222243,"corporation":false,"usgs":false,"family":"Kuhry","given":"Peter","email":"","affiliations":[],"preferred":false,"id":781627,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hugelius, Gustaf 0000-0002-8096-1594","orcid":"https://orcid.org/0000-0002-8096-1594","contributorId":73863,"corporation":false,"usgs":false,"family":"Hugelius","given":"Gustaf","email":"","affiliations":[{"id":25546,"text":"Stockholm University, Sweden","active":true,"usgs":false},{"id":17850,"text":"Dept of Earth System Science, Stanford University, Stanford, CA 94305","active":true,"usgs":false}],"preferred":false,"id":781628,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Koven, Charles","contributorId":218051,"corporation":false,"usgs":false,"family":"Koven","given":"Charles","affiliations":[{"id":39617,"text":"Lawrence Berkeley National Lab","active":true,"usgs":false}],"preferred":false,"id":781629,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lawrence, David M.","contributorId":105206,"corporation":false,"usgs":false,"family":"Lawrence","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":7166,"text":"Johns Hopkins University Applied Physics Laboratory","active":true,"usgs":false}],"preferred":false,"id":781630,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gibson, Carolyn","contributorId":218061,"corporation":false,"usgs":false,"family":"Gibson","given":"Carolyn","email":"","affiliations":[],"preferred":false,"id":781631,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sannel, A. Britta K.","contributorId":222244,"corporation":false,"usgs":false,"family":"Sannel","given":"A.","email":"","middleInitial":"Britta K.","affiliations":[],"preferred":false,"id":781632,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"McGuire, A.D.","contributorId":199633,"corporation":false,"usgs":false,"family":"McGuire","given":"A.D.","email":"","affiliations":[],"preferred":false,"id":781633,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70228637,"text":"70228637 - 2020 - Mapping habitat suitability at range-wide scales: Spatially explicit distribution models to inform conservation and research for marsh birds","interactions":[],"lastModifiedDate":"2022-02-16T21:04:33.98395","indexId":"70228637","displayToPublicDate":"2020-02-03T14:52:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Mapping habitat suitability at range-wide scales: Spatially explicit distribution models to inform conservation and research for marsh birds","docAbstract":"Habitat Loss is a primary cause of species decline, and predicting the distribution of quality habitats across broad scales is needed for conservation of rare species. Secretive marsh birds are a group of emergent-wetland specialists that include multiple threatened and endangered species whose populations have been impacted by wetland loss and modification. Habitat suitability for marsh birds is poorly mapped, and predictions of habitat quality over broad scales are primarily generated via expert judgment. We developed data-driven models to predict fine-resolution habitat quality for 13 marsh bird species across their ranges within the U.S. We demonstrate how these models are useful for conservation by quantifying range contraction, assessing the usefulness of existing protected areas, and assessing the vulnerability of habitats to global change for rare species. These tools provide a quantitative foundation for broad-scale conservation, research, and monitoring efforts, and a starting point for adaptive conservation of marsh bird breeding habitat over broad spatial extents.","language":"English","publisher":"Wiley","doi":"10.1111/csp2.178","usgsCitation":"Stevens, B.S., and Conway, C.J., 2020, Mapping habitat suitability at range-wide scales: Spatially explicit distribution models to inform conservation and research for marsh birds: Conservation Science and Practice, v. 2, no. 4, e178, 8 p., https://doi.org/10.1111/csp2.178.","productDescription":"e178, 8 p.","ipdsId":"IP-113280","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":457877,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.178","text":"Publisher Index Page"},{"id":396039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Stevens, Bryan S.","contributorId":171809,"corporation":false,"usgs":false,"family":"Stevens","given":"Bryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":835048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834900,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209087,"text":"70209087 - 2020 - The Modern Geological Survey; a model for research, innovation, synthjesis: A USGS perspective","interactions":[],"lastModifiedDate":"2020-03-15T14:31:51","indexId":"70209087","displayToPublicDate":"2020-02-03T14:30:52","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"The Modern Geological Survey; a model for research, innovation, synthjesis: A USGS perspective","docAbstract":"Geological Surveys have long filled the role of providing Earth system science data and knowledge. These functions are increasingly complicated by accelerating environmental and societal change. Here we describe the USGS response to these evolving conditions. Underpinning the USGS approach is the recognition that many of the issues facing the U.S. and the world involve the interaction among geologic, hydrologic, and biologic processes, and how these interactions in turn affect society. Therefore, a goal of USGS planning is fostering interdisciplinary science. This focus is occurring in part through implementation of the recommendations of strategic planning teams. The USGS has also put in place groups building a broad information technology infrastructure as well as identifying and disseminating new Earth science research tools. In addition, the USGS has established an analysis and synthesis center that brings together groups of scientists who address interdisciplinary Earth system science issues. The goal is for these building blocks to evolve towards a comprehensive USGS data and knowledge platform; EarthMAP (Earth Monitoring, Assessment, and Projection). We also recognize that the modern geological survey must be a member of a community of geological surveys contributing data to a global database of 3-dimensional biogeophysical observations and interpretations.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Folding and fracturing of rocks: 50 years of research since the seminal text book of J. G. Ramsay","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of London","doi":"10.1144/SP499-2019-250","usgsCitation":"Kimball, S., Goldhaber, M.B., Baron, J., and Labson, V.F., 2020, The Modern Geological Survey; a model for research, innovation, synthjesis: A USGS perspective, chap. of Folding and fracturing of rocks: 50 years of research since the seminal text book of J. G. 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We applied niche overlap analysis to evaluate competition among salmonine predators during rapid forage base change in Lake Michigan. δ13C and δ15N stable isotope ratios indicated that lake trout had a unique trophic niche from inclusion of offshore and benthic prey, with <29% lakewide niche overlap with Chinook salmon, coho salmon and steelhead. Brown trout had moderate overlap with other species (45 – 91%), while Chinook salmon, coho salmon, and steelhead had high overlap (71 – 98%). Regional differences in isotopic signatures highlighted the potential importance of sub-system differences in fish diets in large aquatic systems. The uniqueness of the lake trout niche, and broadness of brown trout and steelhead niches, suggest these species may be resilient to forage base changes. This study demonstrates how niche overlap analysis can be applied to tease apart competitive interactions and their response to ecosystem change.","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2019-0288","usgsCitation":"Kornis, M.S., Bunnell, D.B., Swanson, H.K., and Bronte, C.R., 2020, Spatiotemporal patterns in trophic niche overlap among five salmonines in Lake Michigan, USA: Canadian Journal of Fisheries and Aquatic Sciences, v. 77, no. 6, p. 1059-1075, https://doi.org/10.1139/cjfas-2019-0288.","productDescription":"17 p.","startPage":"1059","endPage":"1075","ipdsId":"IP-111499","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":501017,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/100110","text":"External Repository"},{"id":373201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.814453125,\n 45.90529985724799\n ],\n [\n -85.05615234375,\n 46.210249600187225\n ],\n [\n -85.517578125,\n 46.27103747280261\n ],\n [\n -86.748046875,\n 46.01222384063236\n ],\n [\n -87.71484375,\n 45.398449976304086\n ],\n [\n -88.11035156249999,\n 44.62175409623324\n ],\n [\n -88.11035156249999,\n 44.41808794374846\n ],\n [\n -87.4951171875,\n 44.85586880735725\n ],\n [\n -87.802734375,\n 44.08758502824516\n ],\n [\n -88.13232421875,\n 43.14909399920127\n ],\n [\n -88.13232421875,\n 42.8115217450979\n ],\n [\n -87.978515625,\n 42.22851735620852\n ],\n [\n -87.802734375,\n 41.68932225997044\n ],\n [\n -87.2314453125,\n 41.47566020027821\n ],\n [\n -86.7041015625,\n 41.65649719441145\n ],\n [\n -86.02294921875,\n 42.4234565179383\n ],\n [\n -86.0009765625,\n 43.08493742707592\n ],\n [\n -86.28662109375,\n 43.6599240747891\n ],\n [\n -85.93505859374999,\n 44.38669150215206\n ],\n [\n -85.166015625,\n 44.99588261816546\n ],\n [\n -84.79248046875,\n 45.583289756006316\n ],\n [\n -84.814453125,\n 45.90529985724799\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"77","issue":"6","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kornis, Matthew S.","contributorId":201252,"corporation":false,"usgs":false,"family":"Kornis","given":"Matthew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":784614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B. 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":195888,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","email":"dbunnell@usgs.gov","middleInitial":"B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":784613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swanson, Heidi K.","contributorId":203350,"corporation":false,"usgs":false,"family":"Swanson","given":"Heidi","email":"","middleInitial":"K.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":784615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bronte, Charles R.","contributorId":190727,"corporation":false,"usgs":false,"family":"Bronte","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":784616,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228278,"text":"70228278 - 2020 - Dynamic Habitat Disturbance and Ecological Resilience (DyHDER): Modeling population responses to habitat condition","interactions":[],"lastModifiedDate":"2022-02-08T17:59:30.227932","indexId":"70228278","displayToPublicDate":"2020-02-03T11:56:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic Habitat Disturbance and Ecological Resilience (DyHDER): Modeling population responses to habitat condition","docAbstract":"Understanding how populations respond to spatially heterogeneous habitat disturbance is as critical to conservation as it is challenging. Here, we present a new, free, and open-source metapopulation model: Dynamic Habitat Disturbance and Ecological Resilience (DyHDER), which incorporates subpopulation habitat condition and connectivity into a population viability analysis framework. Modeling temporally dynamic and spatially explicit habitat disturbance of varying magnitude and duration is accomplished through the use of habitat time-series data and a mechanistic approach to adjusting subpopulation vital rates. Additionally, DyHDER uses a probabilistic dispersal model driven by site-specific habitat suitability, density dependence, and directionally dependent connectivity. In the first application of DyHDER, we explore how fragmentation and projected climate change are predicted to impact a well-studied Bonneville cutthroat trout metapopulation in the Logan River (Utah, USA). The DyHDER model predicts which subpopulations are most susceptible to disturbance, as well as the potential interactions between stressors. Further, the model predicts how populations may be expected to redistribute following disturbance. This information is valuable to conservationists and managers faced with protecting populations of conservation concern across landscapes undergoing changing disturbance regimes. The DyHDER model provides a valuable and generalizable new tool to explore metapopulation resilience to spatially and temporally dynamic stressors for a diverse range of taxa and ecosystems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3023","usgsCitation":"Murphy, B.P., Walsworth, T., Belmont, P., Conner, M., and Budy, P., 2020, Dynamic Habitat Disturbance and Ecological Resilience (DyHDER): Modeling population responses to habitat condition: Ecosphere, v. 11, no. 1, e03023, 26 p., https://doi.org/10.1002/ecs2.3023.","productDescription":"e03023, 26 p.","ipdsId":"IP-110023","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":457883,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3023","text":"Publisher Index Page"},{"id":395640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Brendan P.","contributorId":275031,"corporation":false,"usgs":false,"family":"Murphy","given":"Brendan","email":"","middleInitial":"P.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsworth, Timothy E.","contributorId":275032,"corporation":false,"usgs":false,"family":"Walsworth","given":"Timothy E.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belmont, Patrick","contributorId":275033,"corporation":false,"usgs":false,"family":"Belmont","given":"Patrick","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conner, Mary M.","contributorId":275034,"corporation":false,"usgs":false,"family":"Conner","given":"Mary M.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833589,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260140,"text":"70260140 - 2020 - Influence of grain size and shape on volcanic ash electrical conductivity","interactions":[],"lastModifiedDate":"2024-10-29T16:52:16.429331","indexId":"70260140","displayToPublicDate":"2020-02-03T11:49:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Influence of grain size and shape on volcanic ash electrical conductivity","docAbstract":"Few studies have examined the electrical properties of volcanic ash or considered the effects of physical characteristics, such as grain size and shape on its electrification. This study measures the resistivity of eight volcanic ash samples, three milled-samples and five natural ashfall samples from Alaska, U.S.A., using a current amplifier and examines the influence of particle size and particle shape on calculated grain conductivity. Grain conductivities are calculated by applying spherical, oblate, and prolate ellipsoidal shape parameters within a general effective media equation. Volcanic ash is an electrically insulating material with average resistivity values ranging from 1.732E7 to 1.606E12 Ωm. Results show that grain size has a limited impact on resistivity. Calculated grain conductivities remained within the same order of magnitude between the three different shape calculations ranging between 1.367E−7 and 2.196E−12 S/m using the spherical shape parameter. Electrical measurements of heterogeneous powders are complex and challenging. This study aims to expand the community's dataset and understanding of the electrical properties of volcanic ash and the impact of different physical characteristics. This has implication for understanding ash hazards to electrical infrastructure and volcanic lightning.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2020.106788","usgsCitation":"Woods, T., Genareau, K., and Wallace, K.L., 2020, Influence of grain size and shape on volcanic ash electrical conductivity: Journal of Volcanology and Geothermal Research, v. 393, 106788, 9 p., https://doi.org/10.1016/j.jvolgeores.2020.106788.","productDescription":"106788, 9 p.","ipdsId":"IP-101220","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467298,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2020.106788","text":"Publisher Index Page"},{"id":463357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"393","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Woods, Taylor","contributorId":345647,"corporation":false,"usgs":false,"family":"Woods","given":"Taylor","affiliations":[{"id":82675,"text":"The University of Alabama, Tuscaloosa, AL","active":true,"usgs":false}],"preferred":false,"id":917163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Genareau, Kimberly","contributorId":345648,"corporation":false,"usgs":false,"family":"Genareau","given":"Kimberly","affiliations":[{"id":82675,"text":"The University of Alabama, Tuscaloosa, AL","active":true,"usgs":false}],"preferred":false,"id":917164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wallace, Kristi L. 0000-0002-0962-048X kwallace@usgs.gov","orcid":"https://orcid.org/0000-0002-0962-048X","contributorId":3454,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi","email":"kwallace@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917165,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210505,"text":"70210505 - 2020 - Shale gas development has limited effects on stream biology and geochemistry in a gradient-based, multiparameter study in Pennsylvania","interactions":[],"lastModifiedDate":"2020-06-05T15:53:47.823311","indexId":"70210505","displayToPublicDate":"2020-02-03T10:50:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Shale gas development has limited effects on stream biology and geochemistry in a gradient-based, multiparameter study in Pennsylvania","docAbstract":"The number of horizontally drilled shale oil and gas wells in the United States has increased from nearly 28,000 in 2007 to nearly 127,000 in 2017, and research has suggested the potential for the development of shale resources to affect nearby stream ecosystems. However, the ability to generalize current studies is limited by the small geographic scope as well as limited breadth and integration of measured chemical and biological indicators parameters. This study tested the hypothesis that a quantifiable, significant relationship exists between the density of oil and gas (OG) development, increasing streamwater concentrations of known geochemical tracers of OG extraction, and the composition of benthic macroinvertebrate and microbial communities. 25 headwater streams that drain lands across a gradient of shale gas development intensity were sampled. Our strategy included comprehensive measurements across multiple seasons of sampling to account for temporal variability of geochemical parameters, including known shale OG geochemical tracers, and microbial and benthic macroinvertebrate communities. No significant relationships were found between the intensity of OG development, shale OG geochemical tracers, or benthic macroinvertebrate or microbial community composition, whereas significant seasonal differences in stream chemistry were observed. These results highlight the importance of considering spatial and temporal variability in stream chemistry and biota and not only the presence of anthropogenic activities in a watershed. This comprehensive, integrated study of geochemical and biological variability of headwater streams in watersheds undergoing OG development provides a robust framework for examining the effects of energy development at a regional scale.","language":"English","publisher":"PNAS","doi":"10.1073/pnas.1911458117","usgsCitation":"Mumford, A.C., Maloney, K.O., Akob, D., Nettemann, S., Proctor, A., Ditty, J., Ulsamer, L., Lookenbill, J., and Cozzarelli, I.M., 2020, Shale gas development has limited effects on stream biology and geochemistry in a gradient-based, multiparameter study in Pennsylvania: Proceedings of the National Academy of Sciences of the United States of America, v. 117, no. 7, p. 3670-3677, https://doi.org/10.1073/pnas.1911458117.","productDescription":"8 p.","startPage":"3670","endPage":"3677","ipdsId":"IP-108449","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":457886,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1911458117","text":"Publisher Index Page"},{"id":437126,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GJTRYR","text":"USGS data release","linkHelpText":"Sediment composition data from northern Pennsylvania"},{"id":375395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.189453125,\n 40.78054143186033\n ],\n [\n -75.772705078125,\n 40.78054143186033\n ],\n [\n -75.772705078125,\n 42.00848901572399\n ],\n [\n -79.189453125,\n 42.00848901572399\n ],\n [\n -79.189453125,\n 40.78054143186033\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"117","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Mumford, Adam C. 0000-0002-8082-8910 amumford@usgs.gov","orcid":"https://orcid.org/0000-0002-8082-8910","contributorId":171791,"corporation":false,"usgs":true,"family":"Mumford","given":"Adam","email":"amumford@usgs.gov","middleInitial":"C.","affiliations":[{"id":436,"text":"National Research Program - 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Through this collaboration, the model has been updated to include boundary conditions through March 2014 with the most recent water-use data, precipitation and recharge data, and streamflow and water-level observation data. The updated model has been used to evaluate selected alternative water-supply scenarios to determine relative effects on the Mississippi River Valley alluvial aquifer. Alternative water-supply options evaluated in this report include: (1) irrigation efficiency, (2) on-farm storage and tailwater recovery, (3) instream weirs to increase surface-water availability, (4) intrabasin transfer of surface water, and (5) groundwater transfer and injection. A relative comparison approach was used to calculate the simulated water-level response caused by each scenario. Water-level response is the difference between water levels simulated by the alternative water-supply scenario and those simulated by a base or “no action” scenario. Water-level response in the alluvial aquifer varied for each scenario based on the location, magnitude, and (or) adoption rates of the simulated alternative water-supply option. The groundwater transfer and injection scenario showed the largest water-level response.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195116","collaboration":"Prepared in cooperation with the Mississippi Department of Environmental Quality","usgsCitation":"Haugh, C.J., Killian, C.D., and Barlow, J.R.B., 2020, Simulation of water-management scenarios for the Mississippi Delta: U.S. Geological Survey Scientific Investigations Report 2019–5116, 15 p., https://doi.org/10.3133/sir20195116.","productDescription":"Report: iv, 15 p.; Data Release","onlineOnly":"N","ipdsId":"IP-088687","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":399601,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109661.htm"},{"id":371205,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9906VM5","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-2005 model used to evaluate water-management scenarios for the Mississippi Delta"},{"id":371202,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5116/coverthb.jpg"},{"id":371203,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5116/sir20195116.pdf","text":"Report","size":"5.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5116"}],"country":"United States","state":"Arkansas, Louisiana, Mississippi, Missouri","otherGeospatial":"Mississippi River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.69238281249999,\n 36.659606226479696\n ],\n [\n -90.318603515625,\n 35.7019167328534\n ],\n [\n -91.746826171875,\n 33.60546961227188\n ],\n [\n -91.109619140625,\n 32.20350534542368\n ],\n [\n -90.318603515625,\n 32.37996146435729\n ],\n [\n -89.659423828125,\n 33.37641235124676\n ],\n [\n -89.05517578125,\n 34.6241677899049\n ],\n [\n -88.857421875,\n 35.85343961959182\n ],\n [\n -89.69238281249999,\n 36.659606226479696\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, Tennessee 37211
The role of soil biodiversity in regulating multiple ecosystem functions is poorly understood, limiting our ability to predict how soil biodiversity loss might affect human wellbeing and ecosystem sustainability. Here, combining a global observational study with an experimental microcosm study, we provide evidence that soil biodiversity (bacteria, fungi, protists and invertebrates) is significantly and positively associated with multiple ecosystem functions. These functions include nutrient cycling, decomposition, plant production, and reduced potential for pathogenicity and belowground biological warfare. Our findings also reveal the context dependency of such relationships and the importance of the connectedness, biodiversity and nature of the globally distributed dominant phylotypes within the soil network in maintaining multiple functions. Moreover, our results suggest that the positive association between plant diversity and multifunctionality across biomes is indirectly driven by soil biodiversity. Together, our results provide insights into the importance of soil biodiversity for maintaining soil functionality locally and across biomes, as well as providing strong support for the inclusion of soil biodiversity in conservation and management programmes.
","language":"English","publisher":"Nature","doi":"10.1038/s41559-019-1084-y","usgsCitation":"Delgado-Baquerizo, M., Reich, P., Trivedi, M., Eldridge, D.J., Abades, S., Alfaro, F.D., Bastida, F., Berhe, A.A., Cutler, N.A., Gallardo, A., Garcia-Velazquez, L., Hart, S., Hayes, P.E., He, J., Hseu, Z., Hu, H., Kirchmair, M., Neuhauser, S., Perez, C.A., Reed, S.C., Santos, F., Sullivan, B., Trivedi, P., Wang, J., Weber-Grullon, L., Williams, M., and Singh, B.K., 2020, Multiple elements of soil biodiversity drive ecosystem functions across biomes: Nature Ecology and Evolution, v. 4, p. 210-220, https://doi.org/10.1038/s41559-019-1084-y.","productDescription":"11 p.","startPage":"210","endPage":"220","ipdsId":"IP-110876","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":467299,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1784143","text":"External 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marinus)","interactions":[],"lastModifiedDate":"2020-07-13T13:43:01.891684","indexId":"70211049","displayToPublicDate":"2020-02-03T08:40:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":730,"text":"American Journal of Physiology - Regulatory, Integrative and Comparative Physiology","onlineIssn":"1522-1490","printIssn":"0363-6119","active":true,"publicationSubtype":{"id":10}},"title":"Osmoregulatory role of the intestine in the sea lamprey (Petromyzon marinus)","docAbstract":"Lampreys are the most basal vertebrates with an osmoregulatory strategy. Previous research has established that salinity tolerance of sea lamprey increases dramatically during metamorphosis, but underlying changes in the gut have not been examined. In the present work, we examined changes in intestinal function during metamorphosis and seawater exposure of sea lamprey (Petromyzon marinus). Fully metamorphosed sea lamprey had 100 % survival after direct exposure to 35 ppt SW and only slight elevations in plasma chloride (Cl-) levels. Drinking rates of sea lamprey juveniles in seawater were 26-fold higher than juveniles in FW. Na+/K+-ATPase (NKA) activity in the anterior and posterior intestine increased 12- and 3-fold respectively during metamorphosis, whereas esophageal NKA activity was lower than in the intestine and did not change with development. Acclimation to SW significantly enhanced NKA activity in the posterior intestine but did not significantly change NKA activity in the anterior intestine which remained higher than that in the posterior intestine. Intestinal Cl- and water uptake, which was observed in ex vivo preparations of anterior and posterior intestine under both symmetric and asymmetric conditions, were higher in juveniles than in larvae and were similar in magnitude of those of teleost fish. Inhibition of NKA by ouabain in ex vivo preparations inhibited intestinal water absorption by 64 %. Our results suggest drinking and intestinal ion and water absorption are important to osmoregulation in SW, and that preparatory increases in intestinal NKA activity are important to the development of salinity tolerance that occurs during sea lamprey metamorphosis.","language":"English","publisher":"American Physiological Society","doi":"10.1152/ajpregu.00033.2019","usgsCitation":"Barany, A., Shaughnessy, C.A., Fuentes, J., Mancera, J.M., and McCormick, S.D., 2020, Osmoregulatory role of the intestine in the sea lamprey (Petromyzon marinus): American Journal of Physiology - Regulatory, Integrative and Comparative Physiology, v. 318, no. 2, p. 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